MongoDB (MDB) 9 Dec 242025 Q3 Earnings call transcript

Good day, and thank you for standing by. Welcome to the MongoDB Third Quarter Fiscal Year 2025 Conference Call. [Operator Instructions] Please be advised that today's conference is being recorded.

I would now like to turn the call over to your speaker for today, Brian Denyeau. ahead. go Please

issued Good us Lisa. XXXX thank all press you results, market of Thank today. to afternoon, review joining release our in today we fiscal the MongoDB's for close which the you, announced and after third financial quarter

the are me MongoDB; President of Dev and on Joining Michael CFO. Gordon, Ittycheria, CEO and MongoDB's call today COO and

the the to macroeconomic make our our investments statements conditions we financial of landscape, in the this could our will forward-looking financial a our statements, expectations statements AI, operations cause opportunities, risks to that planned differ to call, behaviors, customer actual and for expectations. opportunities and including in of market our product XXXX related environment and future are our fiscal competitive of the materially results growth subject During including AI. platform, impact from These our guidance, of benefits and variety and results uncertainties, growth and

August this Any undertake only XX, SEC statements made to forward-looking update of report results, on obligation quarterly please XXXX, For a the July no actual affect the with for of quarter today, filed required as our to call in law. by on views our we ended reflect material could XXXX. that discussion as we the described and XX, risks Form them, refer our XX-Q on that uncertainties and except risks

measure. reconciliation discuss measures tables of the the will portion of non-GAAP on Investor conference the in a GAAP directly in website comparable to we Additionally, release to measures these for financial most our Please earnings this call. financial our refer Relations

Dev. turn over to like the I'd Dev? to that, With call

of pleased you market business joining Thanks, new opportunity. large a to to and quarter strong everyone I'm for Brian, that well executed our we and against had report today. us thank

our by before third giving update. quarter a broader begin company results reviewing Let's you

generated high the ended a and of with revenue non-GAAP third income over performance guidance. quarter with a XX% we customers. million end $XXX representing pleased operating Overall, Atlas XX% of we are in We above revenue margin, year-over-year grew million, generated $XXX XX% revenue. and the of of We XX% increase our operating year-over-year, the our XX,XXX non-GAAP total for quarter.

a business had happy new with new we're Atlas. We acquisition our strong on and quarter workload

benefited Our significantly few with large we a non-Atlas relationship continue in deals and value build longer-term to because multiyear strategy, as from business part, run our deeper, expectations, exceeded to anywhere customers want MongoDB. a

we would in in Atlas trends as a consumption largely characterize expected will Michael we consistent half detail. more that macro the with the was better first consumption slightly environment cover than of what saw year. in

of will rates the opportunity. believe I strategic want with mission-criticality strong initiatives. to making major in give platform. we those On Retention to QX, our X remained our call, you earnings an us the we're enable shared progress on the update QX on we that initiatives maximize our demonstrating you long-term

the are see returns this the channel in of we we investment strongest the our part in market. increasing First, enterprise since

accounts account strategic going year investment. our more benefit to expanding will Specifically, program incremental next we we're see that as from

investments. of potential. MongoDB To significant these only developers encounter our addition, developers developers enterprise them and how large their organizations incremental simply have full in built know our not these adoption up-level to are fund MongoDB of In and investing applications penetrate benefits to and experience, its In to thousands have deeply, we skills. educate time SQL MongoDB do more we're upmarket accounts resources of of These platform. as developers who and historically we educating investments, the portion we reallocating use on drives a our mid-market

in prioritizing the that The us, strong returns but for investment would opportunity current remains an believe environment. we attractive deliver mid-market upmarket

there believe other customer additional scaled mid-market motions. ways are sales technology-enabled channel self-serve through and serve service and to also efficiently We more our the

the about legacy using this optimistic accelerate are we in opportunity app are to Second, area. modernization investing AI more and

a demonstrating professional successful services recall, that reduce migrating pilots in few combined we to Relational can this on with the cost tooling year, and earlier AI As and product applications Migrator ran legacy risk time, of you significantly our MongoDB.

cost days, modernize. more reduction observed early a it's XX% While have to we than in the

us, and is geography On our the results, customer in every their also additional strong long-term enterprise, are and the enterprises acute infrastructure some opportunity. focus are and important early agile engage demonstrating further these the excited from only for eager to Large they their customers on the most and want size pain exceeding of of cost-effective legacy are to Not level interest back of interest experiencing with more performance in expectations. industry solutions. applications of

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term. to time, that modernization the days our take Although this add app and in scaling motion it's early will have significantly capabilities will we long growth conviction our increased legacy

we emerging technical Third, capitalize investing are key stack. advantages on as AI component tech the to of inherent a our

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the to what market see build effectiveness most in understand the proof-of-concept are From the work customers as and the we today, of underlying early experimental in tech applications. still stack they AI stage

are number have Today, product we What we increasing seeing yet is we fit and, However, of platform. these significant market in apps of production. don't our many thousands actually apps meaningful see of an traction. on AI achieving apps therefore, AI

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will AI we remain grown apps workload see more are usefulness to that the we of product confident one developers happen becomes is some AI that see since will have tech that quickly, has share successful that broadly. our including fit, sophisticated beginning of will Similar XXx our building platform the nail we of shifts, AI more of apps that many but has growing emergence do as more more We do prior use that year. difficult market AI We as and with AI the these a already X-figure improves popular that cost-effective, fair when the it's predict capture platform to applications cases.

Atlas MongoDB enterprise-grade this even We capabilities, momentum investing capture including position to the continue and to our Search opportunity. build Vector better product in functionality AI on

of as to anywhere run Search offerings, world EA addition, our leveraging competitive community Search our in and announced, In previously Vector the we advantage bringing AI. and are

are collaboration services new with Applications a developers MAAP, providers, enterprise AI announced tech we into Unstructured we and Finally, them week, including applications Confluent, MongoDB reference helps leading production cohort Last build using which MongoDB customers to support. Meta Llama. with McKinsey, enable our and expanding Capgemini bring and as of well coordinated to a and AI-enriched partners, on providing as AI or integrations with applications build by Program, architectures,

MongoDB most ever. and I'd the MongoDB product London stringent version X.X, MongoDB benchmarks X.X October, update. provide our most brief you conference XX% built common to industry to of with availability compared to exceed prior and Next, our resiliency, customers' XX% security, better availability developer .local our against requirements. general is the performance fastest and version to At performs announced like performant in we a in of

To best do products from we our to are create we our that, the tiers results to smallest we're the decision desire. that in provides a Atlas consolidate the to made to highest Consequently, showing our with with regularly serve offering ensure Flex investments dedicated products our our we with elasticity akin allocating clusters, and to serverless. deprecate customers, not review new customers. architecture And Atlas portfolio demand offerings to we that serverless also features our product re-prioritize resources simpler a

this in entry-level migrating simple, will single, customers We begin QX. affected to solution

the to other widely our also Device focus adopted We order to in engineering deprecate not decided and on Sync core platform. capabilities resources Atlas

the grow deliver decisions re-prioritization customers, database the allow commitment lightly, reinforcing best the these most number to being made faster. to are of largest our helping and not value us us to to they modern While

minutes to Victoria's full like MongoDB our of Financial power spend Times, including our the projects MongoDB across leveraging the trends I'd running in customer the Customers of data and Atlas, world around industries across Now are and base. developer few platform, CarGurus a Secret. adoption mission-critical reviewing

its As part to of their MongoDB retailer e-commerce Victoria's global Atlas. & Company platform Secret specialty digital migrated transformation journey,

the fully their and experience customers managed mobile retailer and the architecture allowed fast platform, provide secure its and a performance, simplify web a world. for of to improve As resilient, Atlas MongoDB supporting around company to the e-commerce millions

to previous of schema and application turning weeks. metrics. of the with create to proprietary SQL minutes, Altamont solution software, Allianz, applications. MongoDB something MongoDB Xx employee their MongoDB provider take can flexible was leading than power architecture, payroll to Atlas Paylocity, up Swiss to less aimed keep increased traffic Paylocity that original database company's When selected modernize human are take costs and used MongoDB at to fostering developers cloud-based connections advantage and unable now SQL-based an ], engagement. migrated solution. scalability. to performance Paylocity a the and within required performance the to and capital management [ And Post applications the

Mature including Nodes, to efficiency wave concerned tech TealBook companies NerdWallet, which pgvector Cisco eliminate that Search and and various enrich isolation Atlas pgvector migrated issues supplier verify supplier their resolved application inconsistencies, and and stack. the an Postgres, for index in search The data startups scalability MongoDB their dedicated intelligence consolidate technical debt Search data with using scalability the and TealBook, improved and experienced all alike AI migration customers, AI-powered platform, gen MongoDB. help their to and to to the has uses next workload and collect, With cost across supplier from to platform, deliver to with increased realized Vector and a were application were MongoDB Elasticsearch TealBook. of company are sources.

an become In both we in strong to expectations. remain quarter, We saw and increasing had Atlas market. in our provider exceeding summary, we EA strategic and and a growing large business QX with our confident a healthy new ability

we of the adoption Looking application. grow modernizing workloads, see and legacy through next new to enterprise a AI-powered great generation forward, opportunity our in winning the applications,

an I to on would senior finish providing like update leadership. by our

meaningful First, MongoDB's scaling been instrumental revenue over a generate nearly a and XX and leverage. has has Board excited made to to XX-fold, well-deserved break. is -- past as and Michael the press after personal leading and us me take our years, release, we the nearly trusted to the announced successfully and adviser a has partner become scaling over He successful earlier business leave the IPO, been Michael decision our friend. grow model to business years also operating our has Michael Gordon MongoDB. decade, in in success the helping

We have internal commenced we'll search and replacement, both be for candidates. the external Michael's and evaluating

proudest will as accomplishments a miss Michael not under -- continue building his has confident to and finance world-class this a we help serve team CFO that One been compliments transition. beat I'm through XXst not of fiscal January during transition to will a Michael's leadership, adviser by year, seamless Interim beginning of successor Finance, fiscal Serge will to and have If named on to we company the Tanjga, we'll then as CFO SVP to the year-end, February an X. serve process. Michael's finish us ensure

will org particular, Cedric to will the on Cedric field-based, the services. our role newly Pech, to this execute believe enable teams, this the structure I upmarket In professional of increased all congratulate key some new customer-facing and President, in would Operations. of focus Cedric modernization strategic currently created best Worldwide on promoting are opportunity. Revenue including initiatives Chief discussed app earlier, Officer, well-deserved on to oversee we this enablement Field our and go-to-market We like our position, Second, promotion. us I

that, Michael. turn the me call With let over to

of professional potential is what MongoDB and thanks career, most of have still I'm believe continues for proud and success past markets over in realizing of in the Thanks, my our MongoDB whole we decade. one in course, words largest the extremely we've incredible kind take early team. Dev, much past I The XX it share the had, and in been its and, rewarding partnership achieved the years that the full with With the as of stages as as to software. together

I'll turning for the fiscal with third our quarter then our quarter. the outlook begin XXXX. results and Now finish a full to review quarter fourth results detailed for with and of year

our $XXX.X revenue million, the First, guidance. results. with above was Total end start quarter third year-over-year our the high I'll up in of XX% quarter and

and on compared Shifting XX% of grew consumption compared and end the Atlas to third the consumption applications. revenue last quarter. now of that user tied previous to to represent of XX% in our year their platform, in XX% mix. fiscal total recognized We primarily activity closely our quarter to based and XXXX product Atlas the customer quarter is XX% revenue of

some on prior consumption our the quarter. This was basis, of seasonal Let QX, a period. Atlas expected. below muted On growth past consumption year in that was of the consumption more in slightly context year-over-year provide years as year's remains me improvement ahead QX expectations. In than

our Non-Atlas Turning came in significantly expectations. non-Atlas ahead of to revenue.

As success EA and business strong, was we base. have to new existing incremental our Dev into workloads mentioned, continue customer selling

deals. non-Atlas QX large from few multiyear our addition, revenue In a benefited

over know, multiyear higher. non-Atlas ASC the a $XX the you recognize term As start multiyear of contract revenues due of year, XXX, last million Compared of contract. the QX was we component license that entire of to license component to at

Turning growth. to customer

the the third our customer over period. by over over Of our which count, we sequentially, customers, total period. During to ago customer are approximately customers X,XXX bringing count XX,XXX in from up XX,XXX, our grew in base year customer which X,XXX compares ago total direct to X,XXX quarter, is over sales year the

It in is customers Atlas to XX,XXX their total primarily ago our customer addition year which to MongoDB important customer count quarter Atlas, customers in workload. mind XX,XXX over our by in count that driven to the Atlas customers compared period. new being the growth over keep adding EA existing of The growth the at reflects is had end in the in first to

was year on. from $XXX,XXX approximately Continuing ended at net our In period. QX, with ARR MRR, quarter up rate X,XXX We ARR in least annualized XXX%. customers X,XXX in expansion the ago with the and

our unless statement. XX%, Gross down Moving income quarter on noted. million, was the $XXX.X results third basis, flat the I'll a the profit discussing be ago margin a representing otherwise non-GAAP period. versus in gross of which is year

$XXX.X for was guidance versus The operations or ago favorable a very license year the more from for a an is operating high-margin primary revenue quarter reason income operating XX% benefit. XX% operating multiyear outperformance, the margin in Our including third million the our margin to period. results income revenue compared

or of in Net on diluted outstanding ago or net XX.X XX.X average the income to $XX.X million diluted share in was compares the shares outstanding. million This million weighted a year million third income shares based per period. $X.XX on $XX.X weighted quarter $X.XX per share average

flow sheet of and $X.X $X.X free balance This cash, equivalents, million. million in and quarter billion $XX and the approximately in cash third We in short-term ago of quarter. flow cash. After compares principal flow finance into Operating the the consideration cash in with cash restricted lease million liabilities, the was $XX.X taking cash third year in cash expenditures was to repayments free million to the ended period. Turning capital investments $XX.X flow. quarter

million fiscal we we purchases communicated. million we a those still IPvX November QX, this did start we've to as to did $XX previously expect outlay addresses not purchase But and previously year, of in expenditures expected. $XX total incur as In capital making

the our quarter year to like turn for now and I'd full to fiscal outlook fourth XXXX.

$XXX fourth revenue the be range to For million. to quarter, of the we in expect $XXX million

We of in outstanding. estimated to the to be non-GAAP to $XX be income net million range range $X.XX operations expect on million million, in diluted average of non-GAAP share based from $XX to weighted XX.X the per income shares $X.XX and

the shares non-GAAP income expect For Note $X.XX in million share $XXX on XX%. $X.XXX $X.XX guidance for estimated non-GAAP weighted non-GAAP that the from of range to share per and be million, XXXX and be in diluted XX average provision revenue range range $XXX XXXX, full in based non-GAAP the $X.XXX per the operations fourth to million to billion, quarter year fiscal of year net net outstanding. fiscal the approximately we to the include income billion of be income to a to full of tax

around I'll provide our context more updated guidance. now some

by during seasonal consumption, in Atlas of expect driven underlying season. typical to slowdown see moderating holiday we application terms in QX First, usage the a

consumption we Atlas continued deceleration on a Second, expect lower growth of to year-over-year in QX, Atlas remained in year-over-year since basis QX. see

in benefit for a not pattern. non-Atlas which QX. do revenue we Third, to normal we this we deals our QX, which multiyear is additional to experienced contrary that from in to expect expect decline in sequential recur see reason significant in a QX, The is

addition, want some recent of some count go-to-market our customer going color In our reported will product our and of forward. provide product to changes how the impact I growth some on incremental -- recent of

the are First, as we a enterprise resources our the of Dev go-to-market channel. explained, mid-market from to portion reallocating

customer to direct trade-off over As growth higher makes investment sales mid-market forward. reallocation significantly and, dollars growth believe a see result, as this going we a additions so revenue a drive net that direct customer result, fewer time, We will expect of sales sense. it's slower

migrate a them expect but negligible will since expect reported onetime to approximately and very impact on Atlas a customers to our count in Flex. we customers count. X,XXX have over impact These low impact transition revenue customer have see not who to our Flex and do serverless are spending, we clusters QX we our negative as we customer customers introduce automatically to Second, in QX,

our To and summarize, we're quarter business. pleased our especially win ability with third to results new

in a software, number a of our focusing back. in have secular We to of capture our execution share long-term this the of tailwinds, markets with small We'll fastest-growing and opportunity. and investing all judiciously AI on at continue one largest including

open like it to we'd up that, With Operator? questions. to

[Operator coming Stanley. Sanjit Morgan Instructions] for Our from Singh be question first today will of

Michael, solid on a Congrats, career.

to MongoDB. if you fantastic or take do at just you breather. a an see excited absolutely had next excited I'm You run what

what in Atlas congrats, think to least I is but when correct -- at to improvement the the ahead what Relative execution? take questions, with wrong, we if start So expectations. -- doing function quarters? of consumption question in X me guess, what is Is function off in the your I it past consumption of at look of Michael. least we've What's at I'm activity been coming year, sort the beginning of a X seen the to end user has the the improving? driving quarters, of sales modestly the at past of Atlas it sort a

Yes.

different a So few things.

So the seen you about standpoint. seen look is indicated growth would the from I a talked we've What a underlying at of lower what year, see actually we of consumption growth and we think off our if Atlas stable had we've beginning based consumption. we've the at we thought outlook that year-over-year

and guide. incorporated And that's QX -- so our into

our still and on better excuse basis. sorry, have QX the down me, seen it's QX and than We QX, year-over-year QX -- a expectations, but be

really expectations. of core And sort your the Sanjit, year-over-year of I question, of applications. sure of to our want the underlying set the usage to And we're make relative it, confusing so versus the comparative is that not to

ask that have AI total agent question. Yes, to the And then Dev, makes sense. I you

to out for take store mean has needing an context, What start more data roll as AI of to a it operational of actions. agent an going MongoDB tools terms it applications? In its as Agentic have customers to -- set more does

Yes.

data think and are agents, Sierra sorry, do are talk is to create deem think and about -- out you structures. rolled there's agents, Right out agents. But to focused with complex then other being now, I or there's rolling there's projects companies a just some job, tasks. there's that say rich that from able what So to you're really are on task right, when about jobs, agents the like something being deal they to there's

for hierarchies to just understand patterns Now look they that why within important need need insights. able points, isolated models this is but relationships, get essentially don't and to is be to They AI AI real-time the data data. at

if confirmation, be placed get customer to update -- For a a trying because is chat X to example, may any where order needs your kind with to have deal bot querying you they information. bot on real-time of not have the chat they able some minutes someone's ago gotten

use to understanding like with fraud of very like -- detection, be basically to deal chains. You handling able understand cases, do behaviors advanced things need supply to

intricate things understand data to offers. MongoDB consistent are need these with relationships. All You

this. that of are to well believe so And day, we at the the end we handle positioned

thing would that natural say very And Vector and in embedded, the we've way, Search. is Search other I a that

Vector that's OLTP a we're one all have and we other So We text Search, and do an platform just think and we real not database. advantage. search that, offers And no experience.

And so and with AI platforms. the we're leading frameworks integrated

and customers anywhere, again And huge security enterprise-grade regions have on-prem. compliance or and on us. differentiator either cloud XXX a for can run that We is us

our question from will line coming of And Tyler Citi. the Radke next of be

and best, congratulations the all XX years. on Michael,

talked the were some lot challenges And things from the earlier one terms of was the fiscal think Going year. the in this those about I I execution, back recently year mean just past to of workloads that ramping. sales of you a acquired

consumption quality year next into think how in acquisition trended potential curious the does ago? how workload as time of So that about has this look sort you versus ramp a And the year, of this year.

I'll talk made, changes can about we're just talk the trends. doing bit consumption we Michael then Maybe and about the Yes. a little and what

a the were those wanted that some year, volume adjustments are both focus made. on we of quality the the and of we slight workloads. there to having the the think We So changes and make some at did beginning changes we really positive reasonable And impact.

'XX results with these And because far. again, early we're But we're grow Again, workloads know obviously, far, it's 'XX. consumption? declare early start it's But pleased about the so Michael, but to days. so we'll the seeing we and usually fiscal really over victory workloads in time, too into as go fiscal so small good.

Yes.

and cohorts, Tyler. things, few but it's On talked been should our need data about growth of year 'XX we in success we're earlier too just out that of early could about the earlier, continue. The affect those, that seeing the to made some that expectations. differently. we thanks, we does we We I fiscal couple see business. a a fiscal changes line in quarters and cohorts those we're called -- with more in Just slower that tell. our how behave 'XX really They've talked the where new environment new if will say we've business revised

just We and of that have shows with we cohorts But pleased how evolve. initial how piece, grow they those need so been to kind see the that.

follow-up And the on Great. EA side.

you I the strength about know talked if called more new the by you sort you of duration Search introducing And and this do But business. products? like EA? does a indexing impact the about things you in like of feel Stream that customers think way on-prem bigger was simply quarter. you versus one-off? out that onto relative outsized the business was Processing like are driven Maybe impact how could non-Atlas the do duration this the product some You and maybe feel Vector like your towards upside Or unpack year-over-year.

Yes.

that to important wanting of there and people run strategy, success MongoDB. continued from part a their benefit. always to fiscal see an and an that. overall, the we roughly and in There's and anticipating abnormally the customers. being headwind, been continue So increase continue product anywhere We the about It's to we we that component at beginning to $XX multiyear quantified to of EA with were 'XX we've resonate investment the And find had high the range. in we that how amount a year see talked multiyear million of as therefore,

What million is a what saw, few benefited revenue QX a from than in saw little we of on $XX compared accounts, large this we year more at a QX amount about ago. multiyear a that talked to surprising positively we call earlier

as much expecting. So not as headwind been a of had we

not the you. lumpy, healthy of baseline a can multiyear. of which just try sort it people and for out help spikes, with is there's pretty call we Obviously, when for kind But see we understand. dynamics, it these things, kind be call why the flow, And and some especially deal, just and and but large of and a of also try EA, chunky out we XXX meaty

Yes. I just in Tyler, want we business. add, we that to call our what our are investing EA --

with with Search starting does highly we're First, by that whenever One, our things product. benefits of community of Search all That with for couple open anyone a and get us. platform. investing and product, Vector immediately the in starts MongoDB integrated the source they complete

workloads on-prem. who customers even EA, investment so very to capabilities are workloads those committed We then for is customers migrate Two, definitely run run on-prem. some see us running to EA will large or an want strategy. AI We see to very, of lots

cloud, optionality a on-prem, get but So also not the one. be very they to MongoDB in is the just cloud, cross by using compelling

be will Brad question coming next line our Stifel. of Reback from of And the

Dev, And business. started upside? bunch gating think as It's obviously, of next investments, of the the a this you great Michael, margin talked about a about reallocating should run. are phase incremental great some which we Great. about talking given year investment net-net, call been of growth expenses. best you luck. But the

energized which we and are workloads the have as we're again, high something talk on up And by just legacy that's summarize just is think going next now. obviously the drive conviction that very important to about at large AI that year potentially app market invest, something to database future, and to where quite reason that play not we're that's gen and we I for ideal looking we would see being investments long-term modernization, growth. But those I the investments, say on. to apps, ready

program, the of MAAP Atlas? are most up then of healthy EA a great. those going to and Or That's wind And Atlas? workloads on in combination that be will

than Atlas say I in I days. say would days. EA I on early are think would it's, -- of probably side more early again, the the

Vector for once that think technologies we AI in see you'll other the for conjunction Search with happen MongoDB to Atlas. product, MongoDB well use I that see as Obviously, use and of probably I using people say EA you're first on-prem into more Search on-prem. workloads in can introduce cases. But going would AI

be Blair. from will William coming line question of next of the Ader Jason Our

congratulating a Thank Do or and The Michael, decision? workload best you. I'm EA. belabor cloud you, I kind working comment reassessing enterprises rethinking on-prem had fun represents you might on the how be on versus with been of has not strength placement question think, it Yes. is going the in to it of luck. Dev, but

when I enterprises meaningful enterprises, that think about I on-prem. are workloads running still have Well, think large large

workloads. that probably something have now the investments going I [ But in really they own if being they're then to judicious that can the think they ]. And old so. of place, I infrastructure, everything already as to think cloud the their much that about they do they're in good more was investments those ZIRP popular in run go their days their belief where existing would they think customers leverage was assess

of that majority to customers moving of like see the quite are bunch on-prem. European workloads Also, we in cloud. not -- see for lot particularly as Europe, banks running other some reasons, where a We a aggressively their regulatory reasons, still of the

cloud. Asia, aggressively move much people also it seeing -- the varies we're to conversely, where by much region in more So

of it particular the happening that think and on depends on account. on really what's in I industry, dynamics personal geography So

committed to large on-prem. see U.S. mean are things I banks running we also some very

customer strategy to So really good with they They and very cloud, to MongoDB. something feel anywhere move that's build really why we about when if our on-prem. easy run because the do gives varies, choose can And so to and it and optionality. it it's run

SIs, a hiring All investments right. be? would And on the then just investments salespeople? lot strategic enterprise. just in as additional Could Any you're specific more it be Is also on a follow-up making in a working SIs? detail new it Is little more you of those with investing helpful. more get in what might sales

Yes.

high have we quickly the strategic call which We've number mix upside grow a So for of that right that we of we've just seen accounts benefit, us. deploy everyone's when for a of which identified very accounts, number accounts, resources. we think

Now they're resources, sales accounts. additional technical service resources, resources. and ] service resources to additional support necessarily PS be [ customer There those could not better quota-carrying all additional

developers run application, them called developers, And development that do many build them, use is and with accounts. that can limited, is. even design with MongoDB the can educate more either how simple we they for They're we teams think even build that their more what meet easy we sessions an would potentially developer like hackathons particular We these find about or to the looking help show to like app. them the and of with or call education is what the where we'll things are more reviews, quite how experience we can the MongoDB of because them we engage days it

caching database, then integrated database, think and example, an most maybe like like use all in search and a today a vector and is they customers have to for Like MongoDB. database, that a database OLTP

a can it will quickly. on be app educating sudden, more a function long of doubling say, all the I resources it's far simplify to the back-end a we do them just of power simplify if It's for mix manage why it's this down. predicated my really table. MongoDB accounts, that wow, So the everything just infrastructure, really And quota-carrying bring much MongoDB. And that's is on that of more life, the And whole I opens of my on resources. to not easier build we're suite can resources the but of really us, customers up lot opportunities of term so

Fargo. Our Wells will of Nowinski next be Andrew from line the coming question of

nice Okay. a Congrats on quarter.

customer with how example Postgres sort Mongo? that a pg you an think before frequently it off migrated pgvector change -- I type decided And where transition? gave to customer then seeing you to and like rebound-type And a I me, was said issues make of this Postgres, had this didn't how they Meaning was of Postgres. that customer are long a they or their of using was work? chose some You function. they wondering, excuse

Yes.

So not is in business. can't how seeing trend were Postgres, the our a this long that they I you -- is but we're give on specifics this using

and a part source they're XX-year-old databases cetera, of all do. lifting Server, challenges It's types remember, they're technology. and as the open they have but beneficiary shifting because from Postgres have people You database. of to MySQL, Oracle, an they've -- et open SQL And and an databases, other is source database, been -- relational relational same -- and inherent relational the

inflexible. quite They're

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so know all Postgres is moving relational, they everyone platforms. is again, and of people don't off anything kind relational And because other they because those better know default to

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normalize EA million the would QX? just you That $XX be in was had quick QX, in sequentially a impact very If we still maybe helpful. deal follow-up. multiyear And down

strength that saw at the of the the numbers talked the about haven't and of the understand that level in but that given headwind year, year We the full just we we context QX. help guidance, in just beginning to of given trying you

be Lenschow the The next Barclays. question will of from of line Raimo coming

and the And have think on et AI in people strength in of like well? there, pool as and or terms QX, should coming you coming mentioned EA a self-serve, the cetera, the earlier you about If think how -- up -- about projects QX that as as think in up-sell, kind of then bit like you starting mean call? what like cross-sell opportunity of gave it does renewal about we us renewal this you renewal Michael, quarter, little up situation kind

Yes.

renewal about why tends it for called we because pattern, in terms So talking think that's you we be is QX, not of guide would be which is -- multiyear, think quarter. see I it sequentially, where we EA out. expect But EA the in down which typically if large about to a had what about is our we're to such strength

of AI assess But full things, early and And guide multiyear then some of year and view out. hopefully terms those other And we'll to tell. I behaving have to March. help. continue when think In an it's on earlier workloads updated cohorts in obviously, sort our and view I we'll to evolve think comments QX, we will the how the in of terms are made how played the of get also I that

Yes.

if about What projects, there's Perfect. will the Okay. a big you cetera. Dev, And do see of a talk you in persistent can do working then debate which layer AI like database hyperscalers be terms of from -- little to is bit et guys like you all with obviously, around how of Summit, in you and We kind evolving Can the case big a And have your guys like best you bit you. AWS talk cetera. et don't relationship I speak to with Michael, obviously those little partnerships? this? just the

Yes.

you partnership closed a their -- very strong. with show deals ton week. the last as with and they them in past start very first, the engagement large our field has of new quarter, said, products integrations re:Invent remains just of We I'll It had like So very, the and the Bedrock like been some strong. really AWS, to We're doing deals. this some very, of Q

of we in stronger. little I've deals. we're words with Azure, who past, number a one Kernel part OpenAI the largest Azure bit program and Symantec start. what's with including BI, large We're partner of a But as leadership, Visual of ISV Studio. relationship of also in marketplace Studio, Azure-MongoDB person slower a the closed their -- Native been and we never a think Service I has the bunch shared off the start Azure Azure, of the have partners. runs of Fabric, integrations On And Power called deep We Azure's

actually large -- of uptick we've GCP on field, that changes with And that in past where with favorable and that to comp made terms were a GCP co-sells in deals quarter. they some seen we saw we're GCP some MongoDB the -- of working done does we've results QX. closing this handful focused in some

going well. So in quite general, I things are would say

well they bundling offerings. every of, hyperscalers that's in important hyperscalers since AI day candidly, by-the-way their that I been strategy because things potentially question And database their a offering their have terms implied in databases along And I we've predominant was are are an like I they strategy. and then offerings we've have. with guess, not bundling the mean, been your And the decision. X, decision. pretty think It's executed -- against like with

customers understand the our partner especially the performance seeing I think I And as realize it's AI applications. for better hyperscalers data us. said, And and importance are with layer, to of the

And hyperscalers strong. X so partnership all across the is

line of coming will America. Brad from of question next Sills Bank the be The of

X workloads expected? those than you Migrator. on wanted Michael, Search, of bit to I little maybe any next Stream types Congratulations, that's those Is workload Just there Processing, Great. are Vector new your color on faster move. here, new Relational ask one about of ramping. a how ramping

configuration Yes. because about that because needs you like they search scale nodes. expensive. don't to kind if of to capability you're kind your unique nodes of some all on that capability I requirements. the give you the quite And essentially asymmetrically received. Nodes, where of on will rundown case, And can have really products, this a we I'll use Because search-intensive you demand well high. the your -- that introduced a scale search, their tune quite we've of customers seen -- become just mean, you have called is like can groundbreaking new a our Atlas search Search the is new The which asking

for on One of banks customers. corporate the like Atlas to Google-like largest a using data provide Search payments search is world's massive experience

of provider errors. Search invoices A invoice AI-powered and and perform to find leading and scalability performance on power critical. and which a customer-facing So due teams software analytics analysis are accounting end its uses easily to users that so past future, application, hoc allows contain ad invoices Atlas finance there's

search. that's So

it's performance. Vector for us of uptake product to our released requirements by Atlas In Search, first been again, memory available, very, price to we vastly been up actually our year and kind reduces quantization improved the with which XX%, very the allowing vector QX, support workloads going larger has high. since On generally Search, Vector full

multinational and organization and journalists producers verify data tool a created from AI-powered varied For example, designed sources. news summarize vast help efficiently search, and a information gen to

is to global Atlas case firm hybrid that's search to AI Search Vector suggest A leading that's Elasticsearch use end engine suggest and fight built and media leading articles company replaced a with a Search -- fraud, security to to using user recommendation building users. for Vector

so super well. to as see exciting And that's

use commenting out to the on seeing being makes of another also much very life is Demand embed lot easier. so just We're and a in high. hyperscaler, their of streaming Processing rolled it with it customers interest able product. are cases Stream our that MongoDB, We to

technologies And progress on different on natively to new same or products. I we're these to really money the all and solve need risk. for cost making said before, reduces saving the them we're time, eliminates of and bundling to customers capabilities as problem, of have a a lot overall, quite So to do the the pleased -- bunch with bolt

then to focus that be around And Cedric's here I we about be really question exciting. leadership forward? different thinking That's his wanted ask going may a appointment. under should Any that

known responsibilities. this And we I've change. multiple and a last different his X gosh he I really with companies. I -- time. took He is a -- for, X, of CRO until X for think, And interim expansion for years. has Cedric CRO over now, quarters when worked he have Cedric long been No. made an the I like about our at was like

me think to I work companies There's barometer who at top-tier number used leadership. software for or a understanding with I have who worked for sales a me. good other leaders sales of

so role is take. the I'm about to excited Cedric going super And

and the ourselves the database together better to can more to then And under work we changes upmarket, some AI ideal we're Cedric making align gen on apps. on going for that monetization different well positioning also app tightly be organizations so

the Our next Company. of Cikos of coming from will Mike be & line question Needham

all expectations consumption row and more come what's across what's Or improvement I vintages taking it slightly growth better potentially And the this that wanted for quarter we're scope? is to and there than it, missed is get the to apologies being understanding a this geographies? seeing, I now. place in if second concentrated better to again out a trying in the in back Just embedded just but guide.

cold see step different remind Yes. -- to slightly ways. And change it. I'll No, a dicing or we not and bunch it we're good I to you, water And but insights it, would to monitoring whole And slicing throw pleased describe a obviously, And it as without continuing on better, it. broad-based, and was we're it function see. in we'll trying to of or you Mike. have as information better, share

for a follow-up maybe Dev. for And Terrific. quick

we to of holistically the into any the figure for not more even phase, really top think out to a much that is on-prem. phases, it necessarily are are going AI trying production? demonstration some Or to this exploratory in builds parse Is more out? I Q&A. how are to customers connected? there you still the of cost? But of workloads the had and X optimize way Or latency that at think versus and early customers a thinking are question of workloads about their off run function How that the cited looking just Tyler's you is maybe do

No, of of bit I kind a both. little it's think

I think running of to a very part on-prem. are the you have committed big some customers who estate

And means building by run be workloads. cloud that. that definition leveraging and other workload, has need to build AI basically own then they're the if AI GPUs, -- renting providers So to and going access are to it from GPUs then, which customers their they're an also on-prem, they doing

apps MongoDB. have of small. workloads on a as workloads demonstrated and small early we're running very, think prepared the product experimenting. said do market on meaningful have learning, entering More are very of so still in I AI I of more initial and days. thousands But the remarks, is fit, They're very still production. -- them kind we percentage And traction the

leaders with I these becomes start of I senior technology today, building. get see useful, they're But using people AI, chips think are and apps chuckle AI will think the they off. more I as more the I applications and that you'll more versus sophisticated about the take kind bragging applications more as matures -- seeing

very, So tells of big platform that very just you still days we're in this shift. the early it

line Heath will Our next of of be KeyBanc. coming the Eric question from

from on it Michael, a like and on enterprise. Dev is sounds EA greater focus and the call takeaway the

as a structurally ask we that. growth and should healthy And for could just So going future? rethink to EA differently double-digit foreseeable forward business a then if business this early curious think more follow-up the I question than of fiscal 'XX Mike, that the understand at the I of But if still to But workloads. feel and it's quality a cohort 'XX they look cohort identify of level, the fiscal workloads? just high higher separate of

of do the to EA Dev, you terms one first in and... tackle want

so I we mean experience, said, Vector want way MongoDB. I are community integrating many to are it's run And mean strategy. we're the we the say I have for first in Search into they And I and committed we would as investing core first product. very to Yes. full Search where -- experience them anywhere our customers, our

really And so into That are those will EA the clearly then product. start in building out applications. so investing of can, they capabilities we gate, to EA, building transition the

part part And Atlas a because customers. many big compelling typically very of very, big, features fact business it's the we it of new Atlas. still a our But offering engine, and that growth we multi-cloud and is have, a makes big, on our for big already capabilities launch the of

Yes. And of I think early. do think workloads, I the it's in terms

reminder they small folks, although start grow to tend Just for as a quickly.

need out I track the as other done, can with been is time new I the them. But some play to like that happy with we've in are business thing that been new think, we been we've that I said, we've cohorts we add the that think the I only consistent let pleased winning. business we've but we pretty

And our next coming of of line question Power William will be Baird. the from

you services more on sounds feels some to still contributing of and is here. had like would investments. Dev driving think the there think kind great framework I part comments I just quantification could a of second like color if Any be or some on obviously be the around about just Migrator. you get professional what then higher would because you timing it But interest Relational Dev, AI that And the mean, of long-term maybe get and great it touch any opportunity. is to encouraging wonder the that? meaningful question, just for other Michael, way to helping.

Yes.

apps the are just is the tax legacy legacy we're is up so of So cost of and go enough. the happening. confluence seems going a applications after reason opportunity one, that, and about there's excited like these to it events One supporting managing that increasing

road. customers in fact so apps for kick many the Second, who risk, longer that are can can are regulators on running the industries, the the -- down calling systemic they're regulated legacy no these their a they

end also going the some they life. longer because vendors are kick Third, around, can no can of

a able migrate so to people So to so competitive to tech Fourth, those decision your advantage, want they gen predicated that AI proprietary have on to make be to build leverage you and easily. do a a because to data data to applications need and access stack. modern is data, more

applications more for to longer more And for another also so retiring built you And the so modernize. that's reason then or it firm, risk are no those want them with who to have creates and who companies. the just people just

and in schema applications. essentially the the customers way safely very incredibly Given rewriting part all we -- The schema a securely and figuring easily and document that, those from those to help off map relational migrate application. to them hardest out schema. And data a interested a move are the easily could was always

test you the existing results can three, to time. use old can code build use and advent you gen gen Two, AI reverse of what to tests you AI, use analyze significantly as code. AI the same new then the gen then And can to does. to code to One, new code use you engineer test gen the reduce produce can code. this the Now the that now ensure with the AI

my certainly relational if time feel that effort lot you're relational meaningful oh on app, saying, and another all app like modernization. way, and interest And a is customers a moving that's cut creating to of so in a And suddenly already goodness. from doesn't

platform, advantage that to So needs. a platform moving agile, is and we're MongoDB so for excited. modern a And gives performant more the other their more much scalable flexible, them much that's future why

run very, days. We've it's Again, because in a the number time complex working migration of early now in are the gone very This take We're have that process. these of with pilots some process well. customers applications. will

I some X crown at tertiary for of you just was that Tier want the Tier going we our some hey, thing And are that apps these to application. actually, they're because one -- jewels go also look X not or saying, are after They're most us. painful mentioned saying, after

help we committed again, long-term think and very to going also But long-term meaningful to So this, but time, drive is this -- growth. take -- we're this will that's exciting. very us drive

the a we're margin last Will. relative calling the to in capacity it drive we're up. we're the ARR, your part show to the in out professional right, meet is of of that reason And over doing has is workloads, opportunity. the just last because this investment, typically services where impact but demand as seeing will it, to to MongoDB because building that out that that really additional workloads, gross Yes, to sort though order part this it for of the question that's the the We're and to particular And migration. thing, probably new underscore maybe the obvious, is on

I more hope talked before, into time, But going least that. telegraph more. to healthy expect there's to the term, that out just and effectively component as over able wanted to of to a be and at leverage be we've And and human/services to medium we technology about folks. sort initially to

of will question Rudy D.A. of And from Kessinger Davidson. our be next line the coming

QX. you consumption year-over-year slightly I growth growth while And year-over-year believe year, QX slower from of improve quarter, last last ahead the growth said versus down did expectations.

in it QX last And year-over-year slower regard? make for I so but you a in basis Obviously, growth year, QX, I'm on or better a guess QX with could curious or than that year-over-year comment worse? consumption same was stable

the question. Rudy, thanks Yes. for

did out. called stronger that we see out QX QX. that We did how to the than lower see year-over-year called We relative year. a in than haven't smaller growth, QX, as seasonal We talked Usually, specifically about was and rebound. prior we is

So will hopefully, all triangulate. that you help

at least until year we're follow-up. your call another It commentary, now At just got year large applications scale? until still AI the believe least And it application expectation are but some of seeing it on Okay. quick that I at another that I are back that maybe scale. be March. early sounds at QX broad in at just then rollouts like is the many workloads thousands, it's out not said was AI large would point, being a you Dev, guess deployed scale. your at

Yes.

happening think we right? example, today, for a function have I lot compelling a computing have run don't -- of right? designed complex don't today, side what's phones to of a the models. the our the R&D of in AI, for is it model phones, So very Because the horsepower

besides So successful a very ton you say apps very, consumer Claude. see or of don't ChatGPT

of era, hundreds cloud don't the see don't generation first saw or era. right, we or like of the you taking also we mobile of off apps Internet -- So like the the kind like

in days early the So I think AI. we're like of still

that's predict when them them But quickly. we just few production, traction, kind of And have lot see have very see grow lot I And change. can't that them time, apps, very, AI think fairly a on do I rudimentary been will will that we over having fact, change. while apps people so It's seeing of happen. really we're know functionality. a in meaningful. But platform. where a lot we I have of to our going it building And of of them having just very

would And back remarks. ahead. session. I Dev and today's closing call to go you. over concludes that like the Q&A Thank ahead go for turn to Please

with say as strong and EA. go-to-market both QX our Thank enterprise you, pleased to business opportunity and strongest with exceeding where investments. just new I necessary making expectations Atlas standard our the on across largest everyone. returns results a revenue to to expand establish We're the -- we we're really our wanted performance both investments and channel, see the MongoDB

I ourselves encouraged the legacy are progress least, and thank as like XX him as soon. for we're not we but years app Michael his AI for on would last accelerating emerging contributions well ahead, everyone, we'll AI the tech And you, stack Looking to talk both applications. by and greenfield you Thank past AI the with a modernization standard well. wish as again to over making of establishing

Thank you conference participating call. for in today's

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